Phytoconstituents of Withania somnifera unveiled Ashwagandhanolide as a potential drug targeting breast cancer: Investigations through computational, molecular docking and conceptual DFT studies

Breast cancer is the second most common malignancy in females worldwide and poses a great challenge that necessitates the identification of novel therapeutic agents from several sources. This research aimed to study the molecular docking and molecular dynamics simulations of four proteins (such as PDB: 6CBZ, 1FDW, 5GWK and 2WTT) with the selected phytochemicals from Withania somnifera to identify the potential inhibitors for breast cancer. The molecular docking result showed that among 44 compounds, two of them, Ashwagandhanolide and Withanolide sulfoxide have the potential to inhibit estrogen receptor alpha (ERα), 17-beta-hydroxysteroid -dehydrogenase type 1 (17β-HSD1), topoisomerase II alpha (TOP2A) and p73 tetramerization domain that are expressed during breast cancer. The molecular dynamics (MD) simulations results suggested that Ashwagandhanolide remained inside the binding cavity of four targeted proteins and contributed favorably towards forming a stable protein-ligand complex throughout the simulation. Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties confirmed that Ashwagandhanolide is hydrophobic and has moderate intestinal permeability, good intestinal absorption, and poor skin permeability. The compound has a relatively low VDss value (-1.652) and can be transported across ABC transporter and good central nervous system (CNS) permeability but did not easily cross the blood-brain barrier (BBB). This compound does not possess any mutagenicity, hepatotoxicity and skin sensitization. Based on the results obtained, the present study highlights the anticancer potential of Ashwagandhanolide, a compound from W. somnifera. Furthermore, in vitro and in vivo studies are necessary to perform before clinical trials to prove the potentiality of Ashwagandhanolide.

etoposide, and human p73 tetramerization domain were selected in the present study [Sibuh et al., 2021]. The 3D X-Ray crystallographic structures of the selected breast cancer target protein receptors (ERα, 17β-HSD1, TOP2A and p73 tetramerization domain) were retrieved as pdb format from the Protein Data Bank database (https://www.rcsb.org/) (Suppl. Table 1). The protein structures were processed by removing the co-crystallized ligand and water molecules attached to them to avoid unwanted molecular interactions with the target receptors during virtual screening exercise using the Discovery Studio software . The energy minimization, reconstruction of missing atoms and stereo-chemical quality checks of the protein receptors were performed by using the same software.

Validation of protein structure
The quality of protein structure was further validated using the Ramachandran plot by using PROCHECK via PDBsum database (http://www.ebi.ac.uk/thorntonsrv/databases/pdbsum/Generate.html). The plot enables the visualization of highly preferred, preferred, and disallowed phi (φ) and psi (ψ) angles of each amino acid present in the protein . In addition, the protein structure was also checked with the Protein Structure Analysis (ProSA) web tool for protein model quality assessment. The selected protein that showed Z-score within the range of their respective native proteins (for determining the high-quality) validates their quality.

Molecular docking study
The molecular docking analysis of ligands against the target protein receptors were completed by using Autodock Vina which implicated in PyRx [Uppar et al., 2021] and the resulting binding affinities were expressed in kcal/ mol. The grid box (i.e., binding pocket) for the XYZ coordinates was at 60 Å × 60 Å × 60 Å in case of 6CBZ and 1FDW, while it was at 120 Å × 120 Å ×120 Å in 5GWK and 2WTT. The whole target receptors were enclosed within the

Molecular dynamics (MD) simulations
The molecular dynamics (MD) simulations of the complexes of all the four protein receptors with Ashwagandhanolide were carried out to understand the stability of identified ligand molecule with the protein receptors. The MD simulations were performed using the GROMACS 5.1.4 software with the GROMOS96 43A1 force-field. The ligand topology files were created with the help of the PRODRG server. The prepared protein-ligand complex was then solvated in a cubic box of edge length 10 nm around the central SPC water molecule [Prasad et al., 2020;Dharmashekara et al., 2021]. The adequate number of NaCl counter ions and co-ions was added to maintain the electroneutrality of system. The systems were minimized to remove the short contacts and atoms overlaps. The cut-off radius of 0.9 nm was applied for both van der Waals and Coulombic interactions. The Particle Ewald Mesh method was used to describe the long-range electrostatic interactions. The equilibration was done in two steps. At first step, the coordinates of protein-ligand complex were restrained at their respective positions, and the solvent and ions were allowed to relax in the canonical (NVT) ensemble. In the second step, the restraint weights from the protein-ligand complexes were gradually reduced, and the whole system was equilibrated in the isothermal-isobaric (NPT) ensemble. Using the LINCS algorithm, all bonds including hydrogen atoms were restrained. The temperature of system was controlled at 300 K using the Berendsen thermostat while the pressure was maintained at 1 bar using the Parrinello-Rahman barostat. The long production simulations were initiated with configurations collected from the previous equilibration step.
All the systems were simulated for 20 ns in the NPT ensemble, and trajectory frames were saved at every two ps interval [Chadha et al., 2015].

Assessment of Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties
The ADMET was used to predict the absorption, distribution, metabolism and toxicity properties of the selected compounds. These properties are very important during drug development processes for any phytochemicals. The online pkCSM platform was used to investigate the ADMET properties of the potential ligand molecule [Pires et al., 2015].
The following were the predicted ADMET properties: